Linking gas, particulate, and toxic endpoints to air emissions in the Community Regional Atmospheric Chemistry Multiphase Mechanism (CRACMM) version 1.0
Abstract. Chemical mechanisms describe the atmospheric transformations of organic and inorganic species and connect air emissions to secondary species such as ozone, fine particles, and hazardous air pollutants (HAPs) like formaldehyde. Recent advances in our understanding of several chemical systems and shifts in the drivers of atmospheric chemistry warrant updates to mechanisms used in chemical transport models such as the Community Multiscale Air Quality (CMAQ) modeling system. This work builds on the Regional Atmospheric Chemistry Mechanism version 2 (RACM2) and develops the Community Regional Atmospheric Chemistry Multiphase Mechanism (CRACMM) version 1.0, which fully couples the chemistry leading to ozone and secondary organic aerosol (SOA) with consideration of HAPs. CRACMM v1.0 includes 178 gas-phase species, 51 particulate species, and 508 reactions spanning gas-phase and heterogeneous pathways. To support estimation of health risks associated with HAPs, nine species in CRACMM cover 50 % of the total cancer and 60 % of the total noncancer health risk estimated for primary HAPs from anthropogenic and biomass burning sources in the U.S., with the coverage of risk higher (>80 %) when secondary formaldehyde and acrolein are considered. In addition, new mechanism species were added based on the importance of their emissions for ozone, organic aerosol, or atmospheric burden of total reactive organic carbon (ROC): sesquiterpenes, furans, propylene glycol, alkane-like low to intermediate volatility organic compounds (9 species), low to intermediate volatility oxygenated species (16 species), intermediate volatility aromatic hydrocarbons (2 species), and slowly reacting organic carbon. Intermediate and lower volatility organic compounds were estimated to increase the coverage of anthropogenic and biomass burning ROC emissions by 40 % compared to current operational mechanisms. Autoxidation, a gas-phase reaction particularly effective in producing SOA, was added for C10 and larger alkanes, aromatic hydrocarbons, sesquiterpenes, and monoterpene systems including second generation aldehydes. Integrating the radical and SOA chemistry put additional constraints on both systems and enabled the implementation of previously unconsidered SOA pathways from phenolic and furanone compounds, which were predicted to account for ~30 % of total aromatic hydrocarbon SOA under typical atmospheric conditions. CRACMM organic aerosol species were found to span the atmospherically relevant range of carbon number, number of oxygens per carbon, and oxidation state with a slight high bias in number of hydrogens per carbon. In total, eleven new emitted species were implemented as precursors to SOA compared to current CMAQv5.3.3 representations resulting in a bottom-up prediction of SOA, which is required for accurate source attribution and design of control strategies. CRACMMv1.0 will be available in CMAQv5.4.
Havala O. T. Pye et al.
Havala O. T. Pye et al.
Data for the Community Regional Atmospheric Chemistry Multiphase Mechanism (CRACMM) version 1.0 https://doi.org/10.23719/1527956
Model code and software
CMAQ Repository https://github.com/USEPA/CMAQ
CRACMM Repository https://github.com/USEPA/CRACMM
Havala O. T. Pye et al.
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This manuscript developed a new chemical mechanism for 3D chemical transport modeling, CRACMM, which represents a major advance compared with the chemical mechanisms used in previous versions of CMAQ. I believe that the new mechanism will benefit the air quality modeling community, especially the researchers working on O3 and SOA simulations. The manuscript is clearly written. I think it can be accepted for publication after the authors address the following minor comments and suggestions.
(1) CRACMM builds on the implementation of RACM2 chemistry coupled with aerosol chemistry of AERO6. As we know, AERO6 treats both organic and inorganic aerosol chemistry, but this manuscript describes only organic chemistry. Did you treat inorganic aerosol chemistry within or outside of CRACMM?
(2) You simulated aging in addition to the initial oxidation of alkane-like species. Aging changes SOA yields. Are the simulated SOA yields of alkanes still consistent with chamber experiments after aging is considered?
(3) Line 138: Do you mean gaseous L/S/IVOC emissions only, or both gaseous and particle-phase L/S/IVOC emissions?
(4) Line 140: Are any SVOC emissions considered here?
(5) Line 154: What kinds of compounds are these? Can they be IVOC?
(6) Line 180: You assumed equal RO2 reaction rates with HO2 and NO here, but what is the amount of RO2 reacted with HO2 vs NO? The latter determines whether this is a high-NOx or low-NOx condition and hence determines the SOA yields.
(7) Line 190: Which of the three methods did you actually use? Multiple linear regression, exponential/logarithmic equation, or averaging?
(8) Are these alkane-like L/S/IVOC species emitted into just the gas phase, or both gas and particle phases?
(9) Line 372: “The decrease in ððð10(ð¶ð∗) per oxygen in the 2-D VBS box model was set at -2.3”. This is likely the largest volatility decrease one oxygen addition might bring. This is a stronger volatility decrease than the default assumption in the 2D-VBS box model. The authors may want to note this in the manuscript.
(10) Line 387-390: How did you select these species?
(11) Line 401-403: Some products are mapped to aldehydes and some are mapped to ketones. Any science behind this assumption?
(12) Line 459-461: Among the products of furan, the model assumes that only furanone leads to SOA production. Is this true?
(13) Line 516: From R9-R13, it is not clear how furanone was produced from aromatics oxidation.
(14) Line 522-523: Will setting the yields to match high-NOx experimental results lead to an underestimation of SOA yields under low-NOx conditions?
(15) Line 651: It is not clear from the text if the organic peroxide products (OPB) lead to any SOA in the model.
(16) Line 712-714: Does this mean the SOA yields from API oxidation will be much higher under high-NOx conditions than under low-NOx conditions?
(17) Line 772-784: Does this section have anything to do with SOA formation?
(18) Line 1141-1142: I don’t think it is appropriate to define this metric as saturation ratio. I think saturation ratio typically means the ratio of vapor concentration to saturation vapor concentration.